Method, software and system for developing interactive call center agent personas

ABSTRACT

A method, software and system of developing personalities for interactive and/or automated call center applications are provided. According to teachings of the present invention, sample population questionnaires and interviews may be used to identify key personality traits. The impact of the identified key personality traits are then empirically determined. Based on the empirical determination of the key personality traits&#39; impact on customer satisfaction, a plurality of personality profiles may be generated for evaluation. A plurality of application types and voice talents may then be employed to evaluate the impact of each personality profile on customer satisfaction, for different user populations and different types of automated systems. The personality traits for each automated system are preferably rated and reviewed to ensure a system accurately represents the identified key personality traits. The various voice talents may also be evaluated to identify those traits best at conveying a desired personality.

TECHNICAL FIELD OF THE INVENTION

The present invention relates generally to call center technology and,more particularly, to interactive voice-enabled customer servicedelivery.

BACKGROUND OF THE INVENTION

Recent advancements in the area of automated speech recognition (ASR)technology have enabled the development of reliable, speech enabled,self-service applications allowing customers to complete various callcenter tasks using automated systems. One important aspect of a userinterface for ASR applications is the “application personality.” Thepersonality or persona of an ASR application may be generally defined asthe general tone, attitude or mood conveyed by the application's“voice”, vocabulary used, as well as style of interaction, e.g., formal,conversational, directed, etc.

In the past, there have been no well defined or effective methods fordeveloping ASR application personas. In modern practice, to develop anASR application system persona, a speech technology vendor willtypically interview customer delivery personnel within their client'scompany in order to understand the client's ASR applicationexpectations. Based on data gathered, the vendor may then createdemonstrations of several different types of ASR application personasand present the persona demonstrations to a group of stakeholders forselection. Generally, such a method of ASR application system personadevelopment fails to address the needs or expectations of ASRapplication end-users and, therefore, generally fails to gain approvalby its targeted users.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of the present embodiments and advantagesthereof may be acquired by referring to the following description takenin conjunction with the accompanying drawings, in which like referencenumbers indicate like features, and wherein:

FIG. 1 is a schematic diagram depicting one embodiment of atelecommunications system incorporating teachings of the presentinvention;

FIG. 2 is a schematic diagram depicting an alternate embodiment of atelecommunications system incorporating teachings of the presentinvention;

FIG. 3 is a schematic diagram depicting a further embodiment of atelecommunications system incorporating teachings of the presentinvention;

FIG. 4 is a block diagram depicting one embodiment of a call centercustomer service delivery and agent persona development systemincorporating teachings of the present invention; and

FIG. 5 is a flow diagram depicting one embodiment of a method fordeveloping automated speech recognition application personasincorporating teachings of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

Preferred embodiments and their advantages are best understood byreference to FIGS. 1 through 5, wherein like numbers are used toindicate like and corresponding parts.

Referring first to FIG. 1, a schematic diagram of an exemplaryembodiment of a telecommunications system, indicated generally at 10 isshown. Telecommunication system 10 may include communication network 12in communication with one or more gateway devices 14 and 16.Input/output (I/O) devices 18 and 20 are each preferably incommunication with respective gateway devices 14 and 16. Accordingly,I/O devices 18 and 20 may be in selective communication with each othervia gateway devices 14 and 16, and communication network 12.

In one embodiment, communication network 12 may be a public switchedtelephone network (PSTN). In alternate embodiments, communicationnetwork 12 may include a cable telephony network, an IP (InternetProtocol) telephony network, a wireless network, a hybrid Cable/PSTNnetwork, a hybrid IP/PSTN network, a hybrid wireless/PSTN network or anyother suitable communication network or combination of communicationnetworks.

Gateways 14 and 16 preferably provide I/O devices 18 and 20 with anentrance to communication network 12 and may include software andhardware components to manage traffic entering and exiting communicationnetwork 12 and conversion between the communication protocols used byI/O devices 18 and 20 and communication network 12. In some embodiments,gateways 14 and 16 may function as a proxy server and a firewall serverfor I/O devices 18 and 20. In some embodiments, gateways 14 and 16 maybe associated with a router (not expressly shown), operable to direct agiven packet of data that arrives at gateway 14 or 16, and a switch (notexpressly shown), operable to provide a communication path in to and outof gateway 14 or 16.

In the present embodiment, I/O devices 18 and 20 may include a varietyof forms of equipment connected to communication network 12 andaccessible to a user. I/O devices 18 and 20 may be telephones (wirelineor wireless), dial-up modems, cable modems, DSL (digital subscriberline) modems, phone sets, fax equipment, answering machines, set-topboxes, televisions, POS (point-of-sale) equipment, PBX (private branchexchange) systems, personal computers, laptop computers, personaldigital assistants (PDAs), SDRs, other nascent technologies, or anyother appropriate type or combination of communication equipmentavailable to a user. I/O devices 18 and 20 may be equipped forconnectivity to communication network 12 via a PSTN, DSL, cable network,wireless network, or any other appropriate communications channel.

Referring now to FIG. 2, a block diagram of an exemplary embodiment of atelecommunication system 22 is shown. In the exemplary embodiment shown,system 22 preferably includes a PSTN 24 and cable head-end 26 incommunication with cable distribution network 28. PSTN 24 may be inoperable communication with host digital terminal (HDT) 30 and functionto convert signals received from PSTN 24 for transmission over cablenetworks. Host digital terminal 30 and cable head-end 26 may be incommunication with combiner 32. Combiner 32 may communicate datareceived from cable head-end 26 and/or PSTN 24 to cable distributionnetwork 28. Cable distribution network 28 may further communicate datato network interface device 34 to a user via telephone 36, computer 38,television 40 or any other suitable I/O device. Cable head-end 26 mayprovide cable television programming and cable modem communications.Cable head-end 26 typically includes a cable modem termination system(not expressly shown) for sending and receiving digital cable modemsignals.

Referring next to FIG. 3, a block diagram of an exemplary embodiment ofa telecommunication system 42 is shown. This exemplary embodimentgenerally includes interconnected IP network 44, PSTN 46, and cabledistribution networks 48 and 50. IP network 44 may include media gatewaycontroller 52, media gateway 54, and signaling gateway 56. Media gateway54 and signaling gateway 56 may be in operative communication with PSTN46 and facilitate communication of information therebetween. IP network44 may further communicate with cable distribution networks 48 and 50via cable modem termination systems (CMTS) 58 and 60, respectively. CMTS58 and 60 may convert IP packets received from IP Network 44 fortransmission on cable distribution networks 48 and 50 and convertsignals received from cable distribution networks 48 and 50 into IPPackets for transmission to IP Network 44. Cable distribution networks48 and 50 may communicate information with users via network interfaceterminals 62 and 64. Network interface terminals 62 and 64 may providedata services to users through I/O devices such as, telephones 66 and68, computers 70 and 72, and televisions 74 and 76. One or more dataservices may also be provided to a user through PSTN 46 and one or moreI/O devices such as telephone 65.

Telecommunication system 42 of FIG. 3 preferably allows transmission ofservices to be delivered to users where such services include, withoutlimitation, voice over Internet protocol (“VoIP”), video over Internet,video-on-demand over broadband connections, and the ability to viewtelevision and film images as well as broadcasts. In addition, one ofordinary skill will appreciate that other embodiments can be deployedwith many variations in the number and type of I/O devices,communication networks, the communication protocols, system topologies,and myriad other details without departing from the spirit and scope ofthe present invention.

Referring now to FIG. 4, a block diagram illustrating one embodiment ofa call center customer service delivery and agent persona developmentsystem incorporating teachings of the present invention is shown. Whilereference herein is made primarily to a customer service call center andthe development of agent personas therefor, alternate implementations ofteachings of the present invention may be employed without departingfrom the spirit and scope thereof.

Illustrated generally at 100 is one embodiment of a system operable topermit a user to perform one or more transactions via a plurality ofservice agents available from a service center. As illustrated in FIG.4, system 100 preferably includes service or call center 102. Service orcall center 102 may include one or more computing apparatuses 104operably coupled to one or more transaction processing service solutionsor agents 106.

Preferably included in computing apparatus 104, is processor 108.Operably coupled to processor 108 of computing apparatus 104 is memory110. Computing apparatus 104 preferably employs processor 108 and memory110 to execute and store, respectively, one or more instructions of aprogram of instructions.

Also included in computing apparatus 104, as illustrated in FIG. 4, iscommunication interface 112. Communication interface 112 is preferablyoperable to couple computing apparatus 104 and/or service or call center102 to an external communication network 114. According to teachings ofthe present disclosure, communication network 114 may be implemented asa PSTN, a cable telephony network, an IP telephony network, a wirelessnetwork, a hybrid cable/PSTN network, a hybrid IP/PSTN network, a hybridwireless/PSTN network, or any other suitable communication network orcombination of communication networks.

Communication interface 112 preferably cooperates with communicationnetwork 114 and user communication device 116 to permit a user toperform one or more transactions via service center 102. Usercommunication device 116 may be a wireless or wireline telephone,dial-up modem, cable modem, DSL modem, or any other appropriate type orcombination of communication equipment available to a user.

In operation as a customer service delivery solution, service or callcenter 102 preferably permits a user, in their natural language, torequest processing or performance of one or more transactions availablefrom service solutions or agents 106. To enable such processing,computing apparatus 104 may include or have access to one or morestorage devices 118 including one or more programs of instructionssubstantially operable to interpret the intent of a user, identify asolution sought by the user and route the user to an appropriate servicesolution agent.

To aid in the interpretation, identification and routing operations ofservice center 102, storage 118 preferably includes action-object matrix120, look-up table 122, utterance storage 124, prompt library 126, aswell as one or more speech recognition capabilities, such as statisticallanguage modeling engine 128.

In one embodiment of the present invention, computing apparatus 104 ispreferably communicatively coupled to one or more connection switches orredirect devices 130. Connection switch or redirect device 130preferably enables computing apparatus 104, upon determining anappropriate destination for the processing of a user selectedtransaction, to route the user via communication network 132 and,optionally, one or more switches 134, to an appropriate agent or moduleof transaction processing service solution 106.

Transaction processing service solution 106 preferably includes aplurality of agents of modules operable to perform one or moreoperations in association with the processing of a user selectedtransaction. For example, transaction processing service solution 106may include one or more agents or modules operable to perform billingservice solutions 136, repair service solutions 138, option servicesolution 140, basic service solutions 142, as well as other servicesolutions. In addition, the agents or modules implemented in or inassociation with transaction processing service solutions 106 mayinclude, but are not limited to, automated or self-service dataprocessing apparatuses, live technician support (human support), as wellas combinations thereof.

In operation as an aid for developing interactive call center agentpersonas, computing apparatus 104 preferably includes personadevelopment module 144. According to teachings of the present invention,computing apparatus 104 may cooperate with persona development module144 to develop one or more call center automated customer servicedelivery solution or agent personas capable of achieving desired levelsof customer satisfaction. As an alternative to the embodimentillustrated in FIG. 4, a system separate and distinct from the systememployed by a service provider to deliver automated customer servicesolutions may be employed without departing from the spirit and scope ofthe teachings of the present invention. As illustrated in FIG. 4,however, system 102 preferably includes the capability to both aid inthe development of service agent personas as well as in the delivery ofeffective customer service via one or more automated customer serviceagents as well as one or more automated call routing mechanisms to liveagents and/or automated service applications.

As illustrated in FIG. 4, persona development module 144 is preferablyoperably coupled to processor 108. Persona development module 144preferably includes questionnaire and/or interview module 146. As isdescribed below, questionnaire and/or interview module 146 may beemployed to acquire a number of personality traits that a samplepopulation considers desirable and/or undesirable from an automatedservice agent from which they seek transactional assistance. Inaddition, questionnaire and/or interview module 146 may be furtheremployed to obtain from sample population users of service agentpersonas developed in accordance with teachings of the present inventionopinions concerning various aspects of the developed service agentpersonas. Questionnaire and/or interview module 146 may be used in otherrespects without departing from the spirit and scope of teachings of thepresent invention.

Weighting module 148 is preferably also included in persona developmentmodule 144. Weighting module 148 may be used to prioritize or otherwiseorder various personality traits, persona profile evaluations, as wellas other values associated with teachings of the present invention.Greater detail concerning the utility of weighting module 148 isdiscussed below.

Persona profile generator 150 may also be included in one embodiment ofpersona development module 144. In such an embodiment, persona profilegenerator module 150 is preferably operable to create one or moreservice agent persona profiles based on, for example, weightingsobtained from weighting module 148, personality traits obtained fromquestionnaire and/or interview module 146, as well as other factors fromvarious other sources.

Persona profile generator module 150 may leverage one or more personaprofile variables available in persona profile variables library ormodule 152 to create the one or more service agent persona profiles.Persona profile variables library or module 152 may include such personaprofile variables as scripts based on tasks, transactions, emotions,seasonal or geographic concerns, expected user groupings, as well asother characteristics. Persona profile variables library or module 152may also include a number of voice talents which may be leveraged in oneor more persona profiles developed by persona profile generator module150. Persona profile variables library or module 152 may also include avariety of language or dialect selections available to persona profilegenerator module 150.

To determine the effectiveness of a service agent persona developed inaccordance with teachings of the present invention, persona developmentmodule 144 preferably includes sample service modules 154. In testing apersona profile developed for example by persona profile generatormodule 150, the developed persona profile may be used in associationwith the performance of one or more tasks available from sample servicemodule 154. As is discussed in greater detail below with respect to FIG.5, profile evaluation module 156 may be leveraged to combine personaprofiles developed by persona profile generator module 150 and sampleservice module 154 to present to a sample population one or moreprototype persona profiles in simulated transaction environments so asto elicit sample population feedback from actual, although simulated,transactional applications. In one embodiment, profile evaluation module156 may cooperate with questionnaire and/or interview module 146 elicitsample population feedback following sample population utilization ofone or more developed persona profiles in association with one or moresample services available from persona development module 144.Alterations or additions may be made to persona development module 144without departing from the spirit and scope of teachings of the presentinvention.

Referring now to FIG. 5, a flow diagram illustrating one embodiment of amethod for developing automated speech recognition application personasis shown according to teachings of the present invention. In a preferredembodiment, utilization of method 160 in FIG. 5 preferably results inidentification and generation of one or more preferred, optimized andappropriate personas for use in a call center automated speechrecognition application.

After beginning at 162, method 160 preferably proceeds to 164 where aplurality of key personality traits may be identified. In one aspect,the key the personality trait discovery process preferably performed at164 results in the generation, creation and/or selection of one or morepersonality types or profiles based on customer data identifying thosepersonality traits considered to be desirable as well as thosepersonality traits considered undesirable from an automated speechrecognition application.

The identification or determination of key personality traits at 164 maybe performed in a variety of manners. For example, one or morequestionnaires may be presented to a test population, preferably asample population of actual or potential end-users or customers. Thequestionnaires are preferably directed to isolation of those personalitytraits desirable and/or undesirable by the test population in theirinteractions with an ASR application. In addition to, or in lieu of, thequestionnaires, one or more interviews may be conducted with members ofthe designated or selected test population in an effort to identifythose personality traits that should be included in an automated speechrecognition application as well as those personality traits that shouldbe avoided in preferred implementations of automated speech recognitionapplications.

The means by which one or more questionnaires and/or one or moreinterviews may be effected are numerous. For example, one or morequestionnaires and/or one or more interviews with members of a selectedor designated test population may be effected through the use of livequestionnaire takers and/or interviewers. In an alternate embodiment, orin addition to live questionnaire takers and interviewers, one or morequestionnaires and/or one or more interviews may be conducted withmembers of a selected or designated test population using aquestionnaire software application or program implemented and effectedon one or more computer systems. A questionnaire response system thatconducts questionnaires with members of a selected test population viatelephone, as well as via other means. Similarly, interviews may beconducted with members of a selected test population using interviewsoftware or applications implemented on one or more computer systems,automated interview applications available to members of the selected ordesignated test population via a PSTN system, as well as via othermeans.

In one embodiment of the key personality trait identification operationspreferably performed at 164 of method 160, a variety of phases may beimplemented. For example, in a first phase, members of a selected ordesignated test population may be asked to rate a number of personalitytraits, for example, on a scale of one-to-five and ranging from “verydesirable” to “very undesirable.” In requesting test population ratingof various personality traits, members of the test population may beasked for their rating of various personality traits in the context ofwhat personality traits members of the designated test population woulddesire from an automated speech recognition application they sought touse to help them perform one or more transactions. In a second phase,members of a selected or designated test population may be asked to listthose traits felt to be most desirable and most undesirable in anautomated speech recognition application from which they soughtassistance. In a third phase of one implementation of the identificationof key personality traits at 164, members of a selected or designatedtest population may be presented with a plurality of voice prompts froma plurality of different prototypes for a “how to use” self serviceautomated speech recognition application or an alternate embodiment ofan ASR application. After listening to each set of voice prompts,members of the selected or designated test population may be asked torate each prototype based on how strongly the prototype can beassociated with a plurality of key personality traits. In one aspect,the plurality of key personality traits to which members of the testpopulation may be asked to evaluate the voice prompts and prototypes,may be a subset of those key personality traits identified in phase oneabove. Also in phase three, members of the selected or designated testpopulation may be asked, in addition to rating the prototypes withrespect to the various key personality traits, to complete a prototypecustomer satisfaction questionnaire from which a prototype customersatisfaction score may be derived. Assignment of customer satisfactionscores may be performed on a variety of customer satisfaction scales,e.g., one-to-ten, like versus dislike, etc.

After identifying one or more key personality traits at 164, method 160preferably proceeds to 166 where one or more of the key personalitytraits may be weighted. In one aspect, weighting the identified keypersonality traits at 166 may include the performance of a one-way ANOVA(analysis of variance) for each identified personality trait todetermine if a variety of ASR application systems or prototypes differsignificantly with respect to each key personality trait. In addition,the performance of a one-way ANOVA, or other appropriate statisticaltest, on each key personality trait may also be used to identify orindicate whether there exists reliable differences between ASRapplication prototypes with respect to one or more selected keypersonality traits. Further, similar to that analysis performed for eachpersonality trait described above, a one-way ANOVA may be performed andtaken into consideration regarding the customer satisfaction ratingsassigned in phase three above, for example, with regards to how eachcustomer satisfaction rating reflects on each of the plurality ofprototypes presented to members of a selected or designated testpopulation. According to teachings of the present invention, alternativestatistical analysis may be performed on data compiled herein and thepresent invention is not limited to statistical data analysis via aone-way ANOVA.

In addition to the performance of a one-way ANOVA on various results ofthe key personality trait identification operations preferably performedat 164, a regression analysis may also be performed on various dataobtained. For example, in one embodiment, a regression analysis may beconducted to determine or define relationships between one or moreselected, significant or otherwise preferred key personality traits andcustomer satisfaction levels or ratings. In one aspect, a regressionanalysis may be leveraged to identify one or more of the strongest keypersonality trait predictors of customer satisfaction. Additionalweighting methodologies may be applied to data obtained withoutdeparting from the spirit and scope of the present invention.

Following the weighting of key personality traits at 166, method 160preferably proceeds to 168 where one or more personality profiles may bedefined or created. In general, method 160 provides for obtaining datain an attempt to identify the importance of various personality traitsusing a variety of methods. Preferably, the outcome of the applicationof these various methods is to facilitate or enable the definition orcreation of one or more ASR application personas or personalities basedon at least those key personality traits the selected or designated testpopulation have indicated as important. At 168, one or more identifiedkey personality traits may be selected for further examination. In oneembodiment, selection of one or more key personality traits may beperformed in accordance with the results of the weighting operationspreferably performed at 166.

Following selection of one or more traits for further examination,selected key personality traits are preferably assigned to one or moregroups. Assignment to groups may be based on, for example, results froma cluster analysis. For example, a cluster analysis performed on aplurality of selected key personality traits may yield a “professional”cluster including such key personality traits as “professional”,“mature”, “formal” and “intelligent” as well as a “personable” clusterincluding such key personality traits as “personable”, “friendly”, and“fun/interesting”. From the groupings of key personality traitsresulting from, for example, a cluster analysis, one or more ASRapplication prototype personas or personality profiles may be created,defined or otherwise generated.

Definition of a personality profile from a grouping of personalitytraits may be effected through a variety of methods. For example, takinginto consideration the “professional” cluster mentioned above, apersonality profile emphasizing such key personality traits asprofessional, formal and knowledgeable/intelligent may be defined for anASR application which includes prompts using fewer contractions, lessdialogue and taking on a more professional and efficient tone. Inanother example, taking into consideration the characteristics of the“personable” cluster described above, a personable personality profileemphasizing key personality traits including personable, friendly andfun/interesting may be defined for an ASR application personalityprofile using a conversational dialogue style and employing informallanguage. Further, the prompts in a “personable” personality profile maybe more verbose, use contractions and take on a generally more friendlyand helpful tone.

In the development, definition or creation of one or more ASRapplication personality profiles from the selected personality traits at168, key personality traits common to each of the groupings resultingfrom a cluster analysis, for example, may be reflected in each of thedefined or created personality profiles. For example, the keypersonality traits of “mature” and “knowledgeable” may be important tousers of both a “professional” automated speech recognition applicationand users of a “personable” automated speech recognition application.Other methods of defining or creating one or more ASR applicationpersonality profiles from identified personality traits at 168 may beemployed. In addition, various other methods of grouping key personalitytraits identified as desirable by members of a selected test populationmay also be employed without departing from the spirit and scope of thepresent invention.

Following the creation, definition or description of one or more ASRapplication personality profiles at 168, method 160 preferably proceedsto 170 where each personality profile is preferably rated regarding itsability to represent key personality traits and deliver customersatisfaction in one or more automated ASR application systems. In apreferred embodiment, the rating of defined or created personalityprofiles may be performed by presenting the prototype personalityprofiles to members of the selected or designated test populations in aplurality of simulated automated speech recognition applications. In apreferred embodiment, the presentation of prototype personality profilesis preferably performed in one or more simulated automated speechrecognition applications including one or more “automated call routing”automated speech recognition application as well as one or more“how-to-use” automated speech recognition application.

As presented to members of the selected or designated test population,the simulated automated speech recognition applications preferablyinclude a variety of differing characteristics. In a first aspect, eachof the plurality of simulated automated speech recognition applicationsmay employ one or more voice talents. In addition, the plurality ofsimulated automated speech recognition applications, including both theautomated call routing and the how-to-use automated speech recognitionapplications, are designed to simulate a variety of tasks, transactionsor operations to be performed by members of the selected testpopulation, the simulated tasks reflective of those likely to beavailable in an actual call-center implementation.

In presentation to members of the test population, members of theselected or designated test population preferably use each simulatedautomated speech recognition application the same number of times, wherethe number of uses is preferably two or more. Preferably on eachinstance of presentation to members of the selected or designated testpopulation, the simulated automated speech recognition applicationspreferably present different combinations of personality and voicetalent characteristics. Following each use, members of the selected ordesignated test population preferably complete one or more customersatisfaction questionnaires and/or interviews. In addition, followingeach use of the simulated automated speech recognition applications,members of the test population preferably respond to one or morequestionnaires and/or interviews directed at rating the automated speechrecognition application personas or personalities on a plurality ofpersonality traits. In a first aspect, the one or more questionnairesand/or interviews conducted with members of the selected or designatedtest population are preferably directed to confirming that thepersonality profiles and their associated characteristics embodyidentified and/or desired personality traits. In addition, a goal of theone or more questionnaires and/or interviews conducted with members ofthe selected or designated test population may be directed atidentification of additional personality traits to be considered indeveloping a persona for an automated speech recognition application.

Responses to the one or more questionnaires and/or interviews by membersof the selected or designated test population concerning their rating ofeach personality profile and associated automated speech recognitionapplication regarding customer satisfaction may be measured by taking anaverage of the customer satisfaction questionnaire and/or interviewresults. After calculating averages, the averages may be converted intoa percentage score with the scores weighted according to the size of asubject segment of the selected or designated test population. Followingweighting, each personality profile, in light of its associatedautomated speech recognition application, may be evaluated to determinewhether it achieves a desired level of customer satisfaction. Evaluatingwhether a personality profile in light of its associated automatedspeech recognition application meets with expected customer satisfactionlevels, may be determined in accordance with a variety of methodologies.

Method 160 may proceed to 170 and 172 if, at 170, it is determined thata prototype personality profile defined from the selected or identifiedpersonality traits does not achieve a desired level of customersatisfaction or fails to meet one or more desired metrics or benchmarks.At 172, one or more characteristics of a defined, prototype or testingpersonality profile may be altered or varied in an attempt to bring thesample personality profile into accordance with a desired level ofcustomer satisfaction or other desirable trait. Characteristics of apersonality profile that may be changed or varied in an effort toachieve a desired level of customer satisfaction include, but are notlimited to, voice talent, dialogue content, tone, grammar, word choice,as well as myriad other characteristics of the automated speechrecognition application personality profile.

At 174, a varied or redefined prototype or testing personality profilemay be reevaluated to determine whether changes made at 172 bring thevaried personality profile into accordance with a desired level ofcustomer satisfaction or meet other characteristics. At 174, one or moreoperations associated with operations preferably performed at 170 may berepeated to measure the level of customer satisfaction from a varied oraltered automated speech recognition application personality profile.Method 160 may end at 176.

Although the disclosed embodiments have been described in detail, itshould be understood that various changes, substitutions and alterationscan be made to the embodiments without departing from their spirit andscope. For example, one or more of the operations performed in method170 may be repeated until a personality profile or persona meeting adesired or preferred level or customer satisfaction, user completion,efficiency, or other benchmarks or metrics are met. In addition, whilereference herein is made primarily to automated speech recognitionapplications, teachings of the present invention may be applied to thedevelopment of personality profiles or personas for other automatedand/or interactive customer service delivery implementations.

1. A method for developing an automated speech recognition application persona, comprising: identifying personality traits key to customer satisfaction; assigning values to the identified personality traits; defining a plurality of personality profiles based on the assigned values; evaluating measurable customer satisfaction effects associated with each personality profile; rating the personality profiles regarding their ability to represent key personality traits in one or more selected automated systems wherein the rating includes eliciting sample population feedback following sample population utilization of the personality profiles; varying one or more characteristics of the personality profiles; and evaluating the varied personality profile characteristics to identify characteristics most capable of conveying preferred personality traits.
 2. The method of claim 1, further comprising assigning empirical weightings to the identified personality traits using regression analysis.
 3. A method of claim 2, further comprising performing a one-way analysis of variance for each identified personality trait.
 4. The method of claim 2, further comprising performing the regression analysis on the identified personality traits to determine a relationship between the identified personality traits.
 5. The method of claim 1, further comprising identifying the personality traits key to customer satisfaction using interviews with a sample population.
 6. The method of claim 1, further comprising identifying personality traits key to customer satisfaction using questionnaires with a sample population.
 7. The method of claim 1, further comprising varying an application in which a personality profile is to be used to rate the ability of the personality profile to represent the key personality traits of customer satisfaction.
 8. The method of claim 1, further comprising varying characteristics of a test population used to rate the personality profiles regarding an ability to represent the key personality traits in one or more automated systems and in evaluating the varied personality profile characteristics to identify the characteristics most capable of conveying preferred personality traits.
 9. The method of claim 1, further comprising varying one or more verbal characteristics of each personality profile to identify characteristics most capable of conveying preferred personality traits.
 10. A system for developing customer service applications, comprising: at least one processor; memory operably associated with the processor; and a program of instructions storable in the memory and executable by the processor, the program of instructions operable to elicit key personality traits from a sample population, order the key personality traits according to customer satisfaction relevance, create one or more customer service application personality profiles based on the ordered personality traits, evaluate the customer service application personality profiles for a customer satisfaction level determination, and modify one or more aspects of each customer service application personality profile not in accordance with a desired level of customer satisfaction wherein the instructions operable to evaluate include instructions operable to elicit sample population feedback following sample population utilization of the personality profiles.
 11. The system of claim 10, further comprising the program of instructions operable to conduct at least one of a sample population interview and a sample population questionnaire to elicit key personality traits from the sample population.
 12. The system of claim 10, further comprising the program of instruction operable to perform at least one of an analysis of variance and a regression analysis on the key personality traits to order the key personality traits.
 13. The system of claim 10, further comprising the program of instructions operable to modify verbal characteristics of each personality profile to bring the personality profile into accordance with the desired level of customer satisfaction.
 14. The system of claim 10, further comprising the program of instructions operable to modify the personality profiles in accordance with an associated automated customer service application operating environment to achieve the desired level of customer satisfaction.
 15. The system of claim 14, further comprising the program of instructions operable to vary operational aspects of the associated automated customer service application to achieve the desired level of customer satisfaction.
 16. The system of claim 14, further comprising the program of instructions operable to vary one or more goals of the automated customer service application to achieve the desired level of customer satisfaction.
 17. A method for managing an automated speech for developing an automated speech recognition application persona, comprising: identifying a set of personality traits; assigning a set of weighting values to the set of identified personality traits to define a personality profile; defining a set of personality profiles based on the assigned values; and rating the personality profiles based on their respective ability to a predetermined level of customer satisfaction in one or more selected automated systems wherein the rating includes eliciting sample population feedback following sample population utilization of the personality profiles; varying one or more characteristics of the personality profiles; and evaluating the varied personality profile characteristics to identify characteristics most capable of conveying preferred personality traits. 